Analyzing the Performance of “Winner-Take-All” and “Voting-Based” Action Selection Policies within the Two-Resource Problem

  • Orlando Avila-García
  • Lola Cañamero
  • René te Boekhorst
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2801)


The problem of action selection for an autonomous creature implies resolving conflicts between competing behavioral alternatives. These conflicts can be resolved either via competition, following a “winner-take-all” approach, or via cooperation in a “voting-based” approach. In this paper we present two robotic architectures implementing these approaches, and report on experiments we have performed to compare their underlying optimization policies. We have framed this study within the context of the “two-resource problem,” as it provides a widely used standard that favors systematic experimentation, analysis, and comparison of results.


External Stimulus Consummatory Behavior Motivational State Action Selection Basic Cycle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ashby, W.R.: Design for a Brain. Chapman and Hall, London (1952)Google Scholar
  2. 2.
    Avila-García, O., Cañamero, L.: A comparison of Behavior Selection Architectures Using Viability Indicators. In: Proc. International Workshop on Biologically-Inspired Robotics: The Legacy of W. Grey Walter, Bristol HP Labs, UK, August 14–16 (2002)Google Scholar
  3. 3.
    Blumberg, B.: Action Selection in Hamsterdam: Lessons from Ethology. In: Proc. Third Intl. Conf. on Simulation of Adaptive Behavior (SAB 1994). MIT Press, Cambridge (1994)Google Scholar
  4. 4.
    Cañamero, L.D.: Modeling Motivations and Emotions as a Basis for Intelligent Behavior. In: Johnson, W.L. (ed.) Proc. First Intl. Conf. on Autonomous Agents, pp. 148–155. ACM Press, New York (1997)CrossRefGoogle Scholar
  5. 5.
    Cañamero, L., Avila-García, O., Hafner, E.: First Experiments Relating Behavior Selection Architectures to Environmental Complexity. In: Proc. 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2002), pp. 3024–3029. IEEE Computer Society Press, Los Alamitos (2002)CrossRefGoogle Scholar
  6. 6.
    Girard, B., Cuzin, V., Guillot, A., Gurney, K.N., Prescott, T.J.: Comparing a Brain- Inspired Robot Action Selection Mechanism with ‘Winner-Takes-All’. In: Proc. Seventh Intl. Conf. on Simulation of Adaptive Behavior, MIT Press, Cambridge (2002)Google Scholar
  7. 7.
    Maes, P.: A Bottom-Up Mechanism for Behavior Selection in an Artificial Creature. In: Meyer, J.A., Wilson, S.W. (eds.) Proc. First Intl. Conf. on Simulation of Adaptive Behavior, pp. 238–246. MIT Press, Cambridge (1991)Google Scholar
  8. 8.
    McFarland, D.: Experimental Investigation of Motivational State. In: McFarland, D. (ed.) Motivational Control Systems Analysis, pp. 251–282. Academic Press, London (1974)Google Scholar
  9. 9.
    McFarland, D.: Form and function in the temporal organization of behavior. In: Bateson, P., Hinde, R. (eds.) Growing Points in Ethology. Cambridge University Press, Cambridge (1976)Google Scholar
  10. 10.
    McFarland, D., Sibly, R.: The behavioural final common path. Philosophical Transactions of the Royal Society (Series B) 270, 265–293 (1975)CrossRefGoogle Scholar
  11. 11.
    Spier, E., McFarland, D.: Basic Cycles, Utility and Opportunism in Self-Sufficient Robots. Robotics and Autonomous Systems 20, 179–190 (1997)CrossRefGoogle Scholar
  12. 12.
    Spier, E., McFarland, D.: Possibly Optimal Decision Making under Self-Sufficiency and Autonomy. Journal of theoretical biology 189, 317–331 (1997)CrossRefGoogle Scholar
  13. 13.
    Tyrrell, T.: Computational Mechanism for Action Selection. PhD. Thesis, Centre for Cognitive Science, University of Edinburg (1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Orlando Avila-García
    • 1
  • Lola Cañamero
    • 1
  • René te Boekhorst
    • 1
  1. 1.Adaptive Systems Research Group, Department of Computer ScienceUniversity of HertfordshireHatfield, HertsUK

Personalised recommendations